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Dynamic video content moderation and policy evaluation using AWS generative AI services

AWS Machine Learning

Organizations across media and entertainment, advertising, social media, education, and other sectors require efficient solutions to extract information from videos and apply flexible evaluations based on their policies. You can use the solution to evaluate videos against content compliance policies.

Policies 132
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Centralize model governance with SageMaker Model Registry Resource Access Manager sharing

AWS Machine Learning

We recently announced the general availability of cross-account sharing of Amazon SageMaker Model Registry using AWS Resource Access Manager (AWS RAM) , making it easier to securely share and discover machine learning (ML) models across your AWS accounts. We will start by using the SageMaker Studio UI and then by using APIs.

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Manage Amazon SageMaker JumpStart foundation model access with private hubs

AWS Machine Learning

Finally, admins can share access to private hubs across multiple AWS accounts, enabling collaborative model management while maintaining centralized control. SageMaker JumpStart uses AWS Resource Access Manager (AWS RAM) to securely share private hubs with other accounts in the same organization.

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Evolution of Customer Experience in E-Commerce 2023

Lumoa

The evolution of customer experience in e-commerce has grown exponentially since the pandemic making customer experience more important than ever. E-commerce sales are now projected to reach $7.4 Here are the CX trends you can expect to see in 2023 and how to keep your e-commerce business on track with the evolution of CX.

e-support 195
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Dive deep into vector data stores using Amazon Bedrock Knowledge Bases

AWS Machine Learning

Personalized and context-aware retrieval – Vector databases can support personalized and context-aware retrieval in RAG systems. Knowledge bases are essential for various use cases, such as customer support, product documentation, internal knowledge sharing, and decision-making systems. All these steps are managed by Amazon Bedrock.

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Using responsible AI principles with Amazon Bedrock Batch Inference

AWS Machine Learning

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security, privacy, and responsible AI.

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Moderate audio and text chats using AWS AI services and LLMs

AWS Machine Learning

Although voice and text chat often support friendly banter, it can also lead to problems such as hate speech, cyberbullying, harassment, and scams. Social platforms seek an off-the-shelf moderation solution that is straightforward to initiate, but they also require customization for managing diverse policies.

Policies 123